Designing a Smarter Way to Identify   Root Causes with Intelligence Support.

About Project

Root Cause Analysis with Intelligence (RCAI) is a concept-led initiative created to improve how pharmaceutical teams identify and document root causes during investigations. Audree observed that traditional RCA depended heavily on individual experience, varied widely between users, and often repeated the same analysis without learning from past cases.

The goal of RCAI was to design a clear, guided investigation flow from scratch. We mapped the journey from incident initiation to root cause confirmation and CAPA alignment, embedding intelligence where it adds value. This approach helps teams work consistently, reuse past learnings, and produce audit-ready investigations without increasing complexity.

About Project

Pharmaceutical

Team

Varun , S.Madhumala

Subscription Category

Quick win

Project start Year

August 2024

Core Business Challenges

Repeated Investigations With Limited Learning

Similar issues were repeatedly investigated because individual learnings were not captured or shared across investigations.

Inconsistent Root Cause Outcomes

Root cause analysis varied across teams and sites, leading to uneven investigation quality and difficulty in defending outcomes during audits.

Heavy Dependence on Manual Coordination

Investigations required frequent follow ups between QA, QC, and other teams, causing delays and loss of investigation context.

Heavy Dependence on Manual Coordination

Investigations required frequent follow ups between QA, QC, and other teams, causing delays and loss of investigation context.

Our Approach

Mapping the RCAI Investigation Flow

We mapped the RCAI investigation flow from incident initiation to root cause confirmation, introducing guided questions and intelligence led cause suggestions to reduce guesswork. The flow allows users to validate, regenerate, or define causes, ensuring investigations reuse past learnings and continuously improve over time.

Mapping the RCAI Investigation Flow

Designing RCAI Into  a Guided Investigation Workflow

The RCAI process was designed as a single, guided investigation workflow with clear stages from incident initiation to root cause confirmation and CAPA alignment. Structured reasoning and contextual intelligence reduced manual coordination, improved consistency, and strengthened audit readiness across teams.

Structured Workflow for Root Cause Identification

The RCAI workflow became a clear, step-by-step investigation flow from incident initiation to root cause confirmation, removing reliance on fragmented discussions and manual reasoning.

Each team can clearly see:

Investigation context and responses
Suggested and confirmed root causes
Pending validations and next steps

This turns root cause analysis from an experience-driven exercise into a guided, consistent, and defensible investigation workflow.

The RCAI workflow became a clear, step-by-step investigation flow from incident initiation to root cause confirmation, removing reliance on fragmented discussions and manual reasoning.

Each team can clearly see:

Investigation context and responses
Suggested and confirmed root causes
Pending validations and next steps

This turns root cause analysis from an experience-driven exercise into a guided, consistent, and defensible investigation workflow.

The RCAI workflow became a clear, step-by-step investigation flow from incident initiation to root cause confirmation, removing reliance on fragmented discussions and manual reasoning.

Each team can clearly see:

Investigation context and responses
Suggested and confirmed root causes
Pending validations and next steps

This turns root cause analysis from an experience-driven exercise into a guided, consistent, and defensible investigation workflow.

Intelligent Root Cause Suggestions

RCAI uses investigation inputs and historical learnings to suggest relevant probable root causes early in the process. Investigators can validate, refine, or regenerate suggestions instead of starting from a blank slate.

This helps teams reduce guesswork, reuse past insights, and arrive at accurate, defensible root causes faster.

Clear Visual Guidance for Root Cause Identification

Clear investigation stages, cause indicators, and validation states guide users through RCAI, making progress and next steps easy to understand.

RCAI Screen for Structured Investigation Stages

Structured UI for Smarter, Root Cause Identification

The RCAI UI guides each investigation stage with clear visuals and cues, reducing errors and keeping teams aligned throughout the analysis.

Results That Introduced Investigation Lifecycle

Clearer investigation flows, connected RCAI stages, and structured reasoning steps improved investigation speed, reduced errors, and strengthened confidence in root cause decisions.

Improved Root Cause Clarity

Structured investigation stages made it easier for teams to understand, review, and validate root causes, reducing confusion and rework across investigations.

Faster, More Effective Investigations

Intelligent root cause suggestions and clear progression replaced manual back-and-forth, helping teams reach accurate conclusions faster with fewer rework cycles.

Reduced Investigation Repetition

Reuse of past investigation learnings prevented teams from re-analyzing similar quality events repeatedly, saving time and improving overall investigation efficiency.

Faster, More Effective Investigations

Intelligent root cause suggestions and clear progression replaced manual back-and-forth, helping teams reach accurate conclusions faster with fewer rework cycles.

Reduced Investigation Repetition

Reuse of past investigation learnings prevented teams from re-analyzing similar quality events repeatedly, saving time and improving overall investigation efficiency.